This page contains the results of CoNGA analyses.
Results in tables may have been filtered to reduce redundancy,
focus on the most important columns, and
limit length; full tables should exist as OUTFILE_PREFIX*.tsv files.
Here we are assessing overall graph-vs-graph correlation by looking at
the shared edges between TCR and GEX neighbor graphs and comparing
that observed number to the number we would expect if the graphs were
completely uncorrelated. Our null model for uncorrelated graphs is to
take the vertices of one graph and randomly renumber them (permute their
labels). We compare the observed overlap to that expected under this null
model by computing a Z-score, either by permuting one of the graph's
vertices many times to get a mean and standard deviation of the overlap
distribution, or, for large graphs where this is time consuming,
by using a regression model for the
standard deviation. The different rows of this table correspond to the
different graph-graph comparisons that we make in the conga graph-vs-graph
analysis: we compare K-nearest-neighbor graphs for GEX and TCR at different
K values ("nbr_frac" aka neighbor-fraction, which reports K as a fraction
of the total number of clonotypes) to each other and to GEX and TCR "cluster"
graphs in which each clonotype is connected to all the other clonotypes with
the same (GEX or TCR) cluster assignment. For two K values (the default),
this gives 2*3=6 comparisons: GEX KNN graph vs TCR KNN graph, GEX cluster
graph vs TCR KNN graph, and GEX KNN graph vs TCR cluster graph, for each of the
two K values (aka nbr_fracs).
The column to look at is *overlap_zscore*. Higher values indicate more
significant GEX/TCR covariation, with "interesting" levels starting around
zscores of 3-5.
Columns in more detail:
graph_overlap_type: KNN ("nbr") or cluster versus KNN ("nbr") or cluster
nbr_frac: the K value for the KNN graph, as a fraction of total clonotypes
overlap: the observed overlap (number of shared edges) between GEX and TCR
graphs
expected_overlap: the expected overlap under a shuffled null model.
overlap_zscore: a Z-score for the observed overlap computed by subtracting
the expected overlap and dividing by the standard deviation estimated from
shuffling.
overlap
expected_overlap
overlap_mean
overlap_sdev
overlap_zscore
overlap_zscore_fitted
overlap_zscore_source
nodes
calculation_time
calculation_time_fitted
gex_edges
tcr_edges
gex_indegree_variance
gex_indegree_skewness
gex_indegree_kurtosis
tcr_indegree_variance
tcr_indegree_skewness
tcr_indegree_kurtosis
indegree_correlation_R
indegree_correlation_P
nbr_frac
graph_overlap_type
2
4.015326
4.09
2.020371
-1.034463
-1.694141
shuffling
262
0.050308
0.000231
524
524
1.643678
2.098540
5.672902
0.597701
0.878505
0.883814
0.035756
0.564493
0.01
gex_nbr_vs_tcr_nbr
94
84.659004
84.25
9.815676
0.993309
1.276800
shuffling
262
0.105123
0.005581
524
11048
1.643678
2.098540
5.672902
0.189351
-0.069373
-1.056194
-0.057329
0.355340
0.01
gex_nbr_vs_tcr_cluster
97
90.789272
89.61
9.756941
0.757410
1.143899
shuffling
262
0.108160
0.006004
11848
524
0.132700
-0.676264
-1.155820
0.597701
0.878505
0.883814
-0.070397
0.256193
0.01
gex_cluster_vs_tcr_nbr
706
678.590038
678.03
32.549487
0.859307
0.902915
shuffling
262
0.091219
0.039407
6812
6812
1.125553
1.721833
3.070619
0.259437
1.443268
3.280935
-0.004940
0.936571
0.10
gex_nbr_vs_tcr_nbr
1124
1100.567050
1097.45
41.214652
0.644188
0.598449
shuffling
262
0.115277
0.065300
6812
11048
1.125553
1.721833
3.070619
0.189351
-0.069373
-1.056194
-0.019091
0.758411
0.10
gex_nbr_vs_tcr_cluster
1275
1180.260536
1184.02
40.203229
2.263002
3.659651
shuffling
262
0.117067
0.070246
11848
6812
0.132700
-0.676264
-1.155820
0.259437
1.443268
3.280935
-0.011697
0.850540
0.10
gex_cluster_vs_tcr_nbr
graph_vs_graph
Graph vs graph analysis looks for correlation between GEX and TCR space
by finding statistically significant overlap between two similarity graphs,
one defined by GEX similarity and one by TCR sequence similarity.
Overlap is defined one node (clonotype) at a time by looking for overlap
between that node's neighbors in the GEX graph and its neighbors in the
TCR graph. The null model is that the two neighbor sets are chosen
independently at random.
CoNGA looks at two kinds of graphs: K nearest neighbor (KNN) graphs, where
K = neighborhood size is specified as a fraction of the number of
clonotypes (defaults for K are 0.01 and 0.1), and cluster graphs, where
each clonotype is connected to all the other clonotypes in the same
(GEX or TCR) cluster. Overlaps are computed 3 ways (GEX KNN vs TCR KNN,
GEX KNN vs TCR cluster, and GEX cluster vs TCR KNN), for each of the
K values (called nbr_fracs short for neighbor fractions).
Columns (depend slightly on whether hit is KNN v KNN or KNN v cluster):
conga_score = P value for GEX/TCR overlap * number of clonotypes
mait_fraction = fraction of the overlap made up of 'invariant' T cells
num_neighbors* = size of neighborhood (K)
cluster_size = size of cluster (for KNN v cluster graph overlaps)
clone_index = 0-index of clonotype in adata object
conga_score
num_neighbors_gex
num_neighbors_tcr
overlap
overlap_corrected
mait_fraction
clone_index
nbr_frac
graph_overlap_type
cluster_size
gex_cluster
tcr_cluster
va
ja
cdr3a
vb
jb
cdr3b
0.400422
26.0
26.0
8
8
0.0
100
0.1
gex_nbr_vs_tcr_nbr
NaN
3
4
TRAV19*01
TRAJ57*01
CALNEGWKGGSEKLVF
TRBV12-2*01
TRBJ1-2*01
CASSFTGGSSYDYTF
0.628428
26.0
NaN
9
9
0.0
43
0.1
gex_nbr_vs_tcr_cluster
34.0
1
3
TRAV13-1*01
TRAJ28*01
CAAATYSGAGSYQLTF
TRBV20-1*01
TRBJ1-4*01
CSATQGGGKLFF
0.693517
26.0
NaN
7
7
0.0
209
0.1
gex_nbr_vs_tcr_cluster
22.0
3
4
TRAV8-3*01
TRAJ11*01
CAVSDLGYSTLTF
TRBV24-1*01
TRBJ1-5*01
CATSQSRIRQPQYF
0.825420
NaN
26.0
12
12
0.0
13
0.1
gex_cluster_vs_tcr_nbr
57.0
1
3
TRAV12-1*01
TRAJ45*01
CAVRLSANRLTF
TRBV20-1*01
TRBJ2-5*01
CSALAYRETQYF
0.825420
NaN
26.0
12
12
0.0
196
0.1
gex_cluster_vs_tcr_nbr
57.0
1
3
TRAV6*01
TRAJ18*01
CALDMRVRGSTLGKLYF
TRBV20-1*01
TRBJ1-1*01
CSADRSGGITEAFF
0.895093
NaN
26.0
8
8
0.0
160
0.1
gex_cluster_vs_tcr_nbr
29.0
3
4
TRAV38-1*01
TRAJ32*01
CAFMKHLGGYGGSGNKLIF
TRBV13*01
TRBJ1-2*01
CASSPGYRPNYDYTF
tcr_clumping
This table stores the results of the TCR "clumping"
analysis, which looks for neighborhoods in TCR space with more TCRs than
expected by chance under a simple null model of VDJ rearrangement.
For each TCR in the dataset, we count how many TCRs are within a set of
fixed TCRdist radii (defaults: 24,48,72,96), and compare that number
to the expected number given the size of the dataset using the poisson
model. Inspired by the ALICE and TCRnet methods.
Columns:
clump_type='global' unless we are optionally looking for TCR clumps within
the individual GEX clusters
num_nbrs = neighborhood size (number of other TCRs with TCRdist
tcr_db_match
This table stores significant matches between
TCRs in adata and TCRs in the file /scratch.global/ben_testing/conga/conga/data/new_paired_tcr_db_for_matching_nr.tsv
P values of matches are assigned by turning the raw TCRdist
score into a P value based on a model of the V(D)J rearrangement
process, so matches between TCRs that are very far from germline
(for example) are assigned a higher significance.
Columns:
tcrdist: TCRdist distance between the two TCRs (adata query and db hit)
pvalue_adj: raw P value of the match * num query TCRs * num db TCRs
fdr_value: Benjamini-Hochberg FDR value for match
clone_index: index within adata of the query TCR clonotype
db_index: index of the hit in the database being matched
va,ja,cdr3a,vb,jb,cdr3b
db_XXX: where XXX is a field in the literature database
tcr_graph_vs_gex_features
This table has results from a graph-vs-features analysis in which we
look for genes that are differentially expressed (elevated) in specific
neighborhoods of the TCR neighbor graph. Differential expression is
assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
gene.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
log2enr = log2 fold change of gene in neighborhood (will be positive)
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the gene
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
ttest_pvalue_adj
mwu_pvalue_adj
log2enr
gex_cluster
tcr_cluster
feature
mean_fg
mean_bg
num_fg
clone_index
mait_fraction
nbr_frac
graph_type
feature_type
2.244313e-17
5.018759e-25
6.143825
1
3
ENSMMUG00000043894
3.022686
0.244070
35
-1
0.0
0.00
tcr_cluster
gex
7.455134e-03
5.542615e-24
6.143828
0
1
ENSMMUG00000060662
1.944040
0.081275
27
240
0.0
0.10
tcr_nbr
gex
4.682479e-02
4.534282e-21
5.903432
0
1
ENSMMUG00000060662
1.879571
0.088682
27
238
0.0
0.10
tcr_nbr
gex
2.781446e-01
6.682292e-19
5.722198
5
1
ENSMMUG00000060662
1.829304
0.094458
27
243
0.0
0.10
tcr_nbr
gex
2.888083e-01
1.830371e-18
5.641075
0
1
ENSMMUG00000060662
1.806370
0.097093
27
230
0.0
0.10
tcr_nbr
gex
2.850508e-01
2.871732e-18
5.587451
0
1
ENSMMUG00000060662
1.791071
0.098851
27
225
0.0
0.10
tcr_nbr
gex
3.566758e-01
4.967101e-18
5.475248
0
1
ENSMMUG00000060662
1.758713
0.102568
27
228
0.0
0.10
tcr_nbr
gex
3.442440e-01
5.220053e-18
5.483158
0
1
ENSMMUG00000060662
1.761009
0.102304
27
219
0.0
0.10
tcr_nbr
gex
3.458164e-01
6.689329e-18
5.454757
0
1
ENSMMUG00000060662
1.752754
0.103253
27
223
0.0
0.10
tcr_nbr
gex
1.779658e+00
6.207490e-16
5.277266
5
1
ENSMMUG00000060662
1.700546
0.109251
27
227
0.0
0.10
tcr_nbr
gex
1.699862e+00
1.202008e-15
5.223451
2
1
ENSMMUG00000060662
1.684516
0.111093
27
234
0.0
0.10
tcr_nbr
gex
1.482734e+00
1.450578e-15
5.281179
0
1
ENSMMUG00000060662
1.701708
0.109118
27
239
0.0
0.10
tcr_nbr
gex
1.432099e+00
1.749898e-15
5.251437
0
1
ENSMMUG00000060662
1.692864
0.110134
27
224
0.0
0.10
tcr_nbr
gex
1.458250e+00
2.013772e-15
5.250125
0
1
ENSMMUG00000060662
1.692473
0.110179
27
237
0.0
0.10
tcr_nbr
gex
2.926445e-02
4.245694e-14
4.892664
0
1
ENSMMUG00000060662
1.185828
0.073744
47
-1
0.0
0.00
tcr_cluster
gex
6.908012e+00
5.446651e-13
4.922364
0
1
ENSMMUG00000060662
1.593302
0.121573
27
218
0.0
0.10
tcr_nbr
gex
7.862132e+00
8.816225e-13
4.873058
0
1
ENSMMUG00000060662
1.578143
0.123315
27
229
0.0
0.10
tcr_nbr
gex
1.255972e-04
5.976196e-12
5.108541
1
3
ENSMMUG00000043894
2.787112
0.365727
27
121
0.0
0.10
tcr_nbr
gex
1.189078e-03
2.640949e-11
4.851444
4
3
ENSMMUG00000043894
2.663305
0.379952
27
81
0.0
0.10
tcr_nbr
gex
2.735097e-04
3.697337e-11
4.908379
1
3
ENSMMUG00000043894
2.690738
0.376800
27
196
0.0
0.10
tcr_nbr
gex
3.475505e-03
8.382899e-10
4.772083
4
3
ENSMMUG00000043894
2.625058
0.384346
27
147
0.0
0.10
tcr_nbr
gex
6.501781e-03
1.058586e-09
4.711510
2
3
ENSMMUG00000043894
2.595863
0.387700
27
214
0.0
0.10
tcr_nbr
gex
4.080873e-03
1.089854e-09
4.775729
1
3
ENSMMUG00000043894
2.626815
0.384144
27
18
0.0
0.10
tcr_nbr
gex
3.407767e-03
1.945689e-09
4.730350
4
3
ENSMMUG00000043894
2.604943
0.386657
27
24
0.0
0.10
tcr_nbr
gex
3.842020e-03
2.121496e-09
4.723664
1
3
ENSMMUG00000043894
2.601721
0.387027
27
118
0.0
0.10
tcr_nbr
gex
2.045944e-02
3.264041e-09
4.555572
1
3
ENSMMUG00000043894
2.520710
0.396335
27
184
0.0
0.10
tcr_nbr
gex
4.371723e-03
6.842264e-09
4.633070
1
3
ENSMMUG00000043894
2.558056
0.392044
27
15
0.0
0.10
tcr_nbr
gex
2.164265e+00
2.255201e-06
4.111250
1
3
ENSMMUG00000043894
2.307001
0.420889
27
64
0.0
0.10
tcr_nbr
gex
2.079656e+00
2.912219e-06
4.080762
4
3
ENSMMUG00000043894
2.292380
0.422569
27
74
0.0
0.10
tcr_nbr
gex
4.155404e-01
3.661825e-06
4.255085
1
3
ENSMMUG00000043894
2.376070
0.412953
27
22
0.0
0.10
tcr_nbr
gex
1.744567e+00
4.961917e-06
4.109200
1
3
ENSMMUG00000043894
2.306017
0.421002
27
130
0.0
0.10
tcr_nbr
gex
4.828658e-01
6.711579e-06
4.175188
1
3
ENSMMUG00000043894
2.337686
0.417363
27
110
0.0
0.10
tcr_nbr
gex
2.536608e+00
8.200559e-06
4.010442
1
3
ENSMMUG00000043894
2.258687
0.426440
27
68
0.0
0.10
tcr_nbr
gex
1.888240e+00
1.105923e-05
4.017658
1
3
ENSMMUG00000043894
2.262142
0.426043
27
28
0.0
0.10
tcr_nbr
gex
5.773776e-01
1.317929e-05
5.000747
2
5
TRIM23
0.780453
0.036267
3
174
0.0
0.01
tcr_nbr
gex
1.039705e+00
3.031310e-05
3.988643
1
3
ENSMMUG00000043894
2.248252
0.427639
27
79
0.0
0.10
tcr_nbr
gex
4.565668e+00
3.464854e-05
4.025198
1
3
ENSMMUG00000043894
2.265754
0.425628
27
206
0.0
0.10
tcr_nbr
gex
3.560770e-73
5.110138e-05
5.530760
1
7
ENSMMUG00000056910
1.700533
0.092432
3
62
0.0
0.01
tcr_nbr
gex
7.945207e+00
7.666406e-05
3.922797
1
3
ENSMMUG00000043894
2.216758
0.431257
27
250
0.0
0.10
tcr_nbr
gex
3.106427e+00
1.148110e-04
3.982158
1
3
ENSMMUG00000043894
2.245148
0.427995
27
119
0.0
0.10
tcr_nbr
gex
6.064211e+00
2.795210e-04
3.839704
1
3
ENSMMUG00000043894
2.177083
0.435816
27
43
0.0
0.10
tcr_nbr
gex
2.521144e-28
1.952129e-02
4.030483
4
2
ZNF48
0.569399
0.045879
3
23
0.0
0.01
tcr_nbr
gex
9.299052e-01
2.146723e-02
3.877036
4
4
BAG4
0.575650
0.051615
3
91
0.0
0.01
tcr_nbr
gex
1.302097e+00
3.562136e-02
4.029565
0
2
C13H2orf15
0.646091
0.054112
3
21
0.0
0.01
tcr_nbr
gex
1.668233e-03
1.864302e-01
6.022600
0
3
ENSMMUG00000060662
2.935597
0.242402
3
232
0.0
0.01
tcr_nbr
gex
6.000005e-05
4.352498e-01
3.897599
2
5
BRWD3
0.780453
0.076350
3
174
0.0
0.01
tcr_nbr
gex
1.149514e-110
4.611845e-01
3.790806
3
4
ENSMMUG00000049532
0.629644
0.061435
3
94
0.0
0.01
tcr_nbr
gex
1.239246e-04
5.026338e-01
3.732104
4
0
AKT1
0.592910
0.059116
3
155
0.0
0.01
tcr_nbr
gex
3.231656e-01
7.589127e-01
5.612850
1
1
ENSMMUG00000060662
2.681532
0.245344
3
219
0.0
0.01
tcr_nbr
gex
1.487335e-98
1.141779e+00
3.527302
3
4
CHERP
0.629644
0.073305
3
94
0.0
0.01
tcr_nbr
gex
Omitted 10 lines
tcr_graph_vs_gex_features_plot
This plot summarizes the results of a graph
versus features analysis by labeling the clonotypes at the center of
each biased neighborhood with the name of the feature biased in that
neighborhood. The feature names are drawn in colored boxes whose
color is determined by the strength and direction of the feature score bias
(from bright red for features that are strongly elevated to bright blue
for features that are strongly decreased in the corresponding neighborhoods,
relative to the rest of the dataset).
At most one feature (the top scoring) is shown for each clonotype
(ie, neighborhood). The UMAP xy coordinates for this plot are
stored in adata.obsm['X_tcr_2d']. The score used for ranking correlations
is 'mwu_pvalue_adj'. The threshold score for displaying a feature is
1.0. The feature column is 'feature'. Since
we also run graph-vs-features using "neighbor" graphs that are defined
by clusters, ie where each clonotype is connected to all the other
clonotypes in the same cluster, some biased features may be associated with
a cluster rather than a specific clonotype. Those features are labeled with
a '*' at the end and shown near the centroid of the clonotypes belonging
to that cluster.
Image source: emoryPair8Final_tcr_graph_vs_gex_features_plot.png
tcr_graph_vs_gex_features_panels
Graph-versus-feature analysis was used to identify
a set of GEX features that showed biased distributions
in TCR neighborhoods. This plot shows the distribution of the
top-scoring GEX features on the TCR
UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie
Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons).
At most 3 features from clonotype neighbhorhoods
in each (GEX,TCR) cluster pair are shown. The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Points are plotted in order of increasing feature score.
Image source: emoryPair8Final_tcr_graph_vs_gex_features_panels.png
tcr_genes_vs_gex_features
This table has results from a graph-vs-features analysis in which we
look for genes that are differentially expressed (elevated) in specific
neighborhoods of the TCR neighbor graph. Differential expression is
assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
gene.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
log2enr = log2 fold change of gene in neighborhood (will be positive)
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the gene
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
In this analysis the TCR graph is defined by
connecting all clonotypes that have the same VA/JA/VB/JB-gene segment
(it's run four times, once with each gene segment type)
ttest_pvalue_adj
mwu_pvalue_adj
log2enr
gex_cluster
tcr_cluster
feature
mean_fg
mean_bg
num_fg
clone_index
mait_fraction
gene_segment
graph_type
feature_type
6.269412e-17
4.853489e-46
9.062205
0
3
ENSMMUG00000060662
2.554212
0.021946
26
-1
0.0
TRAV8-7
tcr_genes
gex
2.999463e-08
3.610592e-44
10.043410
1
2
ENSMMUG00000062211
3.326379
0.025114
15
-1
0.0
TRBV12-2
tcr_genes
gex
6.511641e-10
1.178803e-31
8.973724
5
2
ENSMMUG00000062085
3.317979
0.051564
15
-1
0.0
TRBV4-3
tcr_genes
gex
1.779122e-46
1.488535e-29
6.679359
1
3
ENSMMUG00000043894
3.228590
0.212323
35
-1
0.0
TRBV20-1
tcr_genes
gex
1.868253e+00
4.198438e-28
10.208363
1
2
ENSMMUG00000063185
3.207270
0.019844
6
-1
0.0
TRBV4-2
tcr_genes
gex
3.882604e+00
4.330226e-26
7.986221
5
3
ENSMMUG00000059325
1.954375
0.023616
13
-1
0.0
TRAV25
tcr_genes
gex
1.531591e+00
1.778148e-11
7.778437
3
5
ENSMMUG00000051385
3.355458
0.118651
6
-1
0.0
TRBV7-4
tcr_genes
gex
1.261532e-01
3.482693e-09
7.808343
2
0
ENSMMUG00000051385
3.462733
0.129158
5
-1
0.0
TRBV7-6
tcr_genes
gex
1.541306e-01
2.908451e-05
5.660920
2
1
ENSMMUG00000056515
3.238345
0.394789
9
-1
0.0
TRBV6-3
tcr_genes
gex
8.653139e-02
5.763194e-02
4.572084
0
6
ENSMMUG00000043894
2.899598
0.543311
8
-1
0.0
TRBV21-1
tcr_genes
gex
8.744927e+00
6.177033e-02
3.117088
4
4
ENSMMUG00000056515
1.773075
0.446913
9
-1
0.0
TRBV10-1
tcr_genes
gex
2.863030e-01
1.179343e-01
4.100708
1
7
ENSMMUG00000056515
2.353249
0.441388
7
-1
0.0
TRBV9
tcr_genes
gex
2.837480e-01
1.199131e-01
6.194817
5
0
ENSMMUG00000056515
3.698022
0.430103
5
-1
0.0
TRBV6-2
tcr_genes
gex
2.583847e-12
2.701260e+00
2.769026
2
0
GPATCH2
0.590825
0.111690
4
-1
0.0
TRAV35
tcr_genes
gex
4.150764e-11
8.588965e+00
2.750653
2
0
MANBA
0.590825
0.113044
4
-1
0.0
TRAV35
tcr_genes
gex
8.748592e-01
9.787085e+00
1.029846
0
0
MATR3
1.264374
0.808449
24
-1
0.0
TRBJ1-4
tcr_genes
gex
tcr_genes_vs_gex_features_panels
Graph-versus-feature analysis was used to identify
a set of GEX features that showed biased distributions
in TCR neighborhoods. This plot shows the distribution of the
top-scoring GEX features on the TCR
UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie
Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons).
At most 3 features from clonotype neighbhorhoods
in each (GEX,TCR) cluster pair are shown. The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Points are plotted in order of increasing feature score.
Image source: emoryPair8Final_tcr_genes_vs_gex_features_panels.png
gex_graph_vs_tcr_features
This table has results from a graph-vs-features analysis in which we
look at the distribution of a set of TCR-defined features over the GEX
neighbor graph. We look for neighborhoods in the graph that have biased
score distributions, as assessed by a ttest first, for speed, and then
by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value
passes an initial threshold (default is 10* the pvalue threshold).
Each row of the table represents a single significant association, in other
words a neighborhood (defined by the central clonotype index) and a
tcr feature.
The columns are as follows:
ttest_pvalue_adj= ttest_pvalue * number of comparisons
ttest_stat= ttest statistic (sign indicates where feature is up or down)
mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons
gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores
tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores
num_fg= the number of clonotypes in the neighborhood (including center)
mean_fg= the mean value of the feature in the neighborhood
mean_bg= the mean value of the feature outside the neighborhood
feature= the name of the TCR score
mait_fraction= the fraction of the skewed clonotypes that have an invariant
TCR
clone_index= the index in the anndata dataset of the clonotype that is the
center of the neighborhood.
ttest_pvalue_adj
ttest_stat
mwu_pvalue_adj
gex_cluster
tcr_cluster
num_fg
mean_fg
mean_bg
feature
mait_fraction
clone_index
nbr_frac
graph_type
feature_type
1.808341e-118
44.463843
0.149465
2.0
2.0
3.0
1.000000
0.115830
TRBJ2-1
0.0
33
0.01
gex_nbr
tcr
7.525556e-115
42.863519
0.305571
5.0
3.0
3.0
1.000000
0.123552
TRBV20-1
0.0
68
0.01
gex_nbr
tcr
7.525556e-115
42.863519
0.305571
1.0
3.0
3.0
1.000000
0.123552
TRBV20-1
0.0
121
0.01
gex_nbr
tcr
7.525556e-115
42.863519
0.305571
4.0
3.0
3.0
1.000000
0.123552
TRBV20-1
0.0
242
0.01
gex_nbr
tcr
2.572694e-01
5.130493
1.547852
1.0
0.0
27.0
-0.047797
-0.307910
kf6
0.0
22
0.10
gex_nbr
tcr
2.966857e-01
-5.061649
2.252206
4.0
3.0
27.0
-2.182790
-1.198783
imhc
0.0
246
0.10
gex_nbr
tcr
gex_graph_vs_tcr_features_plot
This plot summarizes the results of a graph
versus features analysis by labeling the clonotypes at the center of
each biased neighborhood with the name of the feature biased in that
neighborhood. The feature names are drawn in colored boxes whose
color is determined by the strength and direction of the feature score bias
(from bright red for features that are strongly elevated to bright blue
for features that are strongly decreased in the corresponding neighborhoods,
relative to the rest of the dataset).
At most one feature (the top scoring) is shown for each clonotype
(ie, neighborhood). The UMAP xy coordinates for this plot are
stored in adata.obsm['X_gex_2d']. The score used for ranking correlations
is 'mwu_pvalue_adj'. The threshold score for displaying a feature is
1.0. The feature column is 'feature'. Since
we also run graph-vs-features using "neighbor" graphs that are defined
by clusters, ie where each clonotype is connected to all the other
clonotypes in the same cluster, some biased features may be associated with
a cluster rather than a specific clonotype. Those features are labeled with
a '*' at the end and shown near the centroid of the clonotypes belonging
to that cluster.
Image source: emoryPair8Final_gex_graph_vs_tcr_features_plot.png
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
GEX landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_gex' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are GEX clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=26 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie GEX features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the GEX features).
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
TCR landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_tcr' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are TCR clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=26 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie TCR features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the TCR features).
Summary figure for the graph-vs-graph and
graph-vs-features analyses.
Image source: emoryPair8Final_graph_vs_summary.png
gex_clusters_tcrdist_trees
These are TCRdist hierarchical clustering trees
for the GEX clusters (cluster assignments stored in
adata.obs['clusters_gex']). The trees are colored by CoNGA score
with a color score range of 2.62e+00 (blue) to 2.62e-09 (red).
For coloring, CoNGA scores are log-transformed, negated, and square-rooted
(with an offset in there, too, roughly speaking).
Image source: emoryPair8Final_gex_clusters_tcrdist_trees.png
conga_threshold_tcrdist_tree
This is a TCRdist hierarchical clustering tree
for the clonotypes with CoNGA score less than 10.0.
The tree is colored by CoNGA score
with a color score range of 1.00e+01 (blue) to 1.00e-08 (red).
For coloring, CoNGA scores are log-transformed, negated, and square-rooted
(with an offset in there, too, roughly speaking).
Image source: emoryPair8Final_conga_threshold_tcrdist_tree.png
hotspot_features
Find GEX (TCR) features that show a biased
distribution across the TCR (GEX) neighbor graph,
using a simplified version of the Hotspot method
from the Yosef lab.
DeTomaso, D., & Yosef, N. (2021).
"Hotspot identifies informative gene modules across modalities
of single-cell genomics."
Cell Systems, 12(5), 446–456.e9.
PMID:33951459
Columns:
Z: HotSpot Z statistic
pvalue_adj: Raw P value times the number of tests (crude Bonferroni
correction)
nbr_frac: The K NN nbr fraction used for the neighbor graph construction
(nbr_frac = 0.1 means K=0.1*num_clonotypes neighbors)
Z
pvalue_adj
feature
feature_type
nbr_frac
31.600037
2.721964e-215
ENSMMUG00000060662
gex
0.10
29.992100
9.182532e-194
ENSMMUG00000043894
gex
0.10
13.770920
2.814559e-39
ENSMMUG00000062085
gex
0.10
13.705246
6.971152e-39
ENSMMUG00000060662
gex
0.01
13.146993
1.307013e-35
ENSMMUG00000043894
gex
0.01
12.224595
1.695591e-30
ENSMMUG00000062211
gex
0.10
11.804036
2.745959e-28
ENSMMUG00000056910
gex
0.10
9.669365
3.003285e-18
ENSMMUG00000059325
gex
0.10
9.167617
3.569391e-16
ENSMMUG00000056910
gex
0.01
8.977690
2.040930e-15
ENSMMUG00000056515
gex
0.10
8.938303
2.916925e-15
ENSMMUG00000013725
gex
0.01
8.899772
4.130520e-15
ARHGAP24
gex
0.01
7.093737
9.635035e-09
ENSMMUG00000059325
gex
0.01
6.688777
1.661048e-07
ENSMMUG00000061119
gex
0.01
5.886012
2.920119e-05
NRTN
gex
0.01
5.878370
3.058139e-05
TNS2
gex
0.01
5.835053
3.969021e-05
ENSMMUG00000056783
gex
0.01
5.720882
7.821851e-05
GSTO2
gex
0.01
5.700405
8.821984e-05
ENSMMUG00000062085
gex
0.01
5.656015
1.143521e-04
LKAAEAR1
gex
0.01
5.259207
1.067868e-03
C4H6orf132
gex
0.01
5.148158
1.941622e-03
ENSMMUG00000061119
gex
0.10
4.909238
6.748512e-03
ENSMMUG00000052673
gex
0.01
4.853287
8.962868e-03
ENSMMUG00000062211
gex
0.01
4.805447
1.139671e-02
MORN4
gex
0.01
4.794499
1.203710e-02
FGD4
gex
0.01
4.753354
1.476717e-02
ENSMMUG00000063055
gex
0.01
4.678995
2.127831e-02
ENSMMUG00000056515
gex
0.01
3.501573
2.937006e-02
TRBV19
tcr
0.01
4.601451
3.096756e-02
PLCB1
gex
0.01
hotspot_gex_umap
HotSpot analysis (Nir Yosef lab, PMID: 33951459)
was used to identify a set of GEX (TCR) features that showed biased
distributions in TCR (GEX) space. This plot shows the distribution of the
top-scoring HotSpot features on the GEX
UMAP 2D landscape. The features are ranked by adjusted P value
(raw P value * number of comparisons). The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Features are filtered based on correlation coefficient to reduce
redundancy: if a feature has a correlation of >= 0.9
(the max_feature_correlation argument to conga.plotting.plot_hotspot_umap)
to a previously plotted feature, that feature is skipped.
Points are plotted in order of increasing feature score
Image source: emoryPair8Final_hotspot_combo_features_0.100_nbrs_gex_plot_umap_nbr_avg.png
hotspot_gex_clustermap
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
GEX landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_gex' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are GEX clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=26 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie GEX features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the GEX features).
HotSpot analysis (Nir Yosef lab, PMID: 33951459)
was used to identify a set of GEX (TCR) features that showed biased
distributions in TCR (GEX) space. This plot shows the distribution of the
top-scoring HotSpot features on the TCR
UMAP 2D landscape. The features are ranked by adjusted P value
(raw P value * number of comparisons). The raw scores for each feature
are averaged over the K nearest neighbors (K is indicated in the lower
right corner of each panel) for each clonotype. The min and max
nbr-averaged scores are shown in the upper corners of each panel.
Features are filtered based on correlation coefficient to reduce
redundancy: if a feature has a correlation of >= 0.9
(the max_feature_correlation argument to conga.plotting.plot_hotspot_umap)
to a previously plotted feature, that feature is skipped.
Points are plotted in order of increasing feature score
Image source: emoryPair8Final_hotspot_combo_features_0.100_nbrs_tcr_plot_umap_nbr_avg.png
hotspot_tcr_clustermap
This plot shows the distribution of significant
features from graph-vs-features or HotSpot analysis plotted across the
TCR landscape. Rows are features and columns are
individual clonotypes. Columns are ordered by hierarchical clustering
(if a dendrogram is present above the heatmap) or by a 1D UMAP projection
(used for very large datasets or if 'X_pca_tcr' is not present in
adata.obsm_keys()). Rows are ordered by hierarchical clustering with
a correlation metric.
The row colors to the left of the heatmap show the feature type
(blue=TCR, orange=GEX). The row colors to the left of those
indicate the strength of the graph-vs-feature correlation
(also included in the feature labels to the right of the heatmap;
keep in mind that highly significant P values for some features may shift
the colorscale so everything else looks dark blue).
The column colors above the heatmap are TCR clusters
(and TCR V/J genes if plotting against the TCR landscape). The text
above the column colors provides more info.
Feature scores are Z-score normalized and then averaged over the
K=26 nearest neighbors (0 means no nbr-averaging).
The 'coolwarm' colormap is centered at Z=0.
Since features of the same type (GEX or TCR) as the landscape and
neighbor graph (ie TCR features) are more highly
correlated over graph neighborhoods, their neighbor-averaged scores
will show more extreme variation. For this reason, the nbr-averaged
scores for these features from the same modality as the landscape
itself are downscaled by a factor of
rescale_factor_for_self_features=0.33.
The colormap in the top left is for the Z-score normalized,
neighbor-averaged scores (multiply by 3.03
to get the color scores for the TCR features).